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91
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IJAR
2008
119views more  IJAR 2008»
15 years 11 days ago
Adapting Bayes network structures to non-stationary domains
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
Søren Holbech Nielsen, Thomas D. Nielsen
JMLR
2010
134views more  JMLR 2010»
14 years 7 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...
AIPS
1996
15 years 1 months ago
Event-Based Decompositions for Reasoning about External Change in Planners
An increasing number of planners can handle uncertainty in the domain or in action outcomes. However, less work has addressed building plans when the planner's world can chan...
Jim Blythe
107
Voted
CVPR
1997
IEEE
16 years 2 months ago
Representation Of Objects In A Volumetric Frequency Domain With Application To Face Recognition
A novel method for representing 3-D objects that unifies viewer and model centered object representations is presented. A unified 3-D frequency-domain representation (called Volum...
Jezekiel Ben-Arie, Dibyendu Nandy
80
Voted
DSL
2009
14 years 10 months ago
Varying Domain Representations in Hagl
Abstract. Experimental game theory is an increasingly important research tool in many fields, providing insight into strategic behavior through simulation and experimentation on ga...
Eric Walkingshaw, Martin Erwig